Search Results (1,116)

This paper investigates the abnormal combustion behavior—specifically knock and pre-ignition—of a hydrogen direct-injection (H₂-DI) engine operated under stoichiometric conditions. Two different cylinder head configurations with central and lateral injector placement are analyzed using thermodynamic measurements, CFD simulations, and the optical diagnostic system VISIOLution^®. The results show that combustion stability and knock tendency are significantly influenced by injector positioning, injection pressure, and ignition timing. Controlled mixture formation and high turbulence during the compression phase are key to achieving both high power density and thermal efficiency in hydrogen-fueled engines. Full article

Closed-loop geothermal systems (CLGSs) avoid groundwater production and offer stable deep heat supply, but their long-term performance hinges on reliable coupling between the wellbore, the near-well interface and the surrounding formation. Using the D22 well in the Xiongan New Area (deep carbonate reservoir), we built a three-domain thermo-hydraulic framework that updates CO₂ properties with temperature and pressure and explicitly accounts for wellbore-formation thermal resistance. Two geometries (U-tube and single-well coaxial) and two working fluids (CO₂ and water) were compared and optimized under field constraints. With the coaxial configuration, CO₂ delivers an average thermal power of 186.3 kW, exceeding that of water by 44.9%, while the fraction of wellbore heat loss drops by 3–5%. Under field-matched conditions, the predicted outlet temperature (76.8 °C) agrees with the measured value (77.2 °C) within 0.52%, confirming the value of field calibration for parameter transferability. Long-term simulations indicate that after 30 years of continuous operation the outlet temperature decline remains <8 °C for CO₂, outperforming water and implying better reservoir utilization and supply stability. Sensitivity and Pareto analyses identify a practical operating window, i.e., flow velocity of 0.9–1.1 m s⁻¹ and depth of 3000–3500 m, favoring the single-well coaxial + CO₂ scheme. These results show how field-calibrated modeling narrows uncertainty and yields implementable guidance on geometry, operating conditions, and wellbore insulation strategy. This study provides quantitative evidence that CO₂-CLGSs in deep carbonate formations can simultaneously increase thermal output and limit long-term decline, supporting near-term engineering deployment. Full article

The rapid advances in artificial intelligence (AI) and high-performance computing (HPC) are transforming the landscape of engineering design, and the concentrated solar power (CSP) tower sector is no exception. As these technologies increasingly penetrate the energy domain, they bring new capabilities for addressing the complex, multi-variable nature of receiver design and optimisation. This review explores the application of AI-driven generative design techniques in the context of CSP tower receivers, with a particular focus on the use of metaheuristic algorithms and machine learning models. A structured classification is presented, highlighting the most commonly employed methods, such as Genetic Algorithms (GAs), Particle Swarm Optimisation (PSO), and Artificial Neural Networks (ANNs), and mapping them to specific receiver types: cavity, external, and volumetric. GAs are found to dominate multi-objective optimisation tasks, especially those involving trade-offs between thermal efficiency and heat flux uniformity, while ANNs offer strong potential as surrogate models for accelerating design iterations. The review also identifies existing gaps in the literature and outlines future opportunities, including the integration of high-fidelity simulations and experimental validation into AI design workflows. These insights demonstrate the growing relevance and impact of AI in advancing the next generation of high-performance CSP receiver systems. Full article

Sand-based thermal energy storage systems represent a paradigm shift in sustainable energy solutions, leveraging Earth’s most abundant mineral resource through advanced nanocomposite engineering. This review examines sand-based phase change materials (PCM) systems with emphasis on integration with human-powered energy generation (HPEG). Silicon-based hierarchical pore structures provide multiscale thermal conduction pathways while achieving PCM loading capacities exceeding 90%. Carbon-based nanomaterial doping enhances thermal conductivity by up to 269%, reaching 3.1 W/m·K while maintaining phase change enthalpies above 130 J/g. This demonstrated cycling stability exceeds 1000 thermal cycles with <8% capacity degradation. Thermal energy storage costs reach ~$20 kWh⁻¹—60% lower than lithium-ion systems when normalized by usable heat capacity. Integration with triboelectric nanogenerators achieves 55% peak mechanical-to-electrical conversion efficiency for direct pathways, while thermal-buffered systems provide 8–12% end-to-end efficiency with temporal decoupling between intermittent human power input and stable electrical output. Miniaturized systems target off-grid communities, offering 5–10× cost advantages over conventional batteries for resource-constrained deployments. Levelized storage costs remain competitive despite efficiency penalties versus lithium-ion alternatives. Critical challenges, including thermal cycling degradation, energy-power density trade-offs, and environmental adaptability, are systematically analyzed. Future directions explore biomimetic multi-level pore designs, intelligent responsive systems, and distributed microgrid implementations. Full article

The downsized Wankel rotary engine (WRE) fueled with methanol is a promising power source for small unmanned aerial vehicles, owing to its simple structure, high-speed capability, and clean emissions. In general, a well-designed ignition timing (IT) can drastically enhance engine combustion performance. To assess the impact of IT, a numerical simulation study was conducted on a methanol-fueled WRE, analyzing its combustion characteristics and emissions to guide performance optimization. The results indicated that advancing the IT boosted the flame propagation velocity. The peak pressure increased slightly when delaying the IT from −24 °CA to −15 °CA but dropped sharply for −12 °CA at 5000 RPM. This contrasts with the behavior at 11,000 RPM and 17,000 RPM, where peak pressure clearly rose with advanced IT. Indicated thermal efficiency (ITE) decreased with the delay of the IT at 11,000 RPM and 17,000 RPM; the maximum values reached 24.98% and 25.78%, respectively. This contrasted with the trend observed at 5000 RPM, where ITE first increased and then decreased with IT delay. The optimized IT significantly affects pollutant emissions primarily under low-speed conditions (5000 RPM), while exhibiting limited impact at high engine speeds. At 5000 RPM, strategic IT adjustment achieves maximum reductions of 2% in CO emissions and 33% in formaldehyde emissions. Full article

Vibration-based predictive maintenance is an essential element of reliability engineering for modern automotive powertrains including internal combustion engines, hybrids, and battery-electric platforms. This review synthesizes advances in sensing, signal processing, and artificial intelligence that convert raw vibration into diagnostics and prognostics. It characterizes vibration signatures unique to engines, transmissions, e-axles, and power electronics, emphasizing order analysis, demodulation, and time–frequency methods that extract weak, non-stationary fault content under real driving conditions. It surveys data acquisition, piezoelectric and MEMS accelerometry, edge-resident preprocessing, and fleet telemetry, and details feature engineering pipelines with classical machine learning and deep architectures for fault detection and remaining useful life prediction. In contrast to earlier reviews focused mainly on stationary industrial systems, this review unifies vibration analysis across combustion, hybrid, and electric vehicles and connects physics-based preprocessing to scalable edge and cloud implementations. Case studies show that this integrated perspective enables practical deployment, where physics-guided preprocessing with lightweight models supports robust on-vehicle inference, while cloud-based learning provides cross-fleet generalization and model governance. Open challenges include disentangling overlapping sources in compact e-axles, coping with domain and concept drift from duty cycles, software updates, and aging, addressing data scarcity through augmentation, transfer, and few-shot learning, integrating digital twins and multimodal fusion of vibration, current, thermal, and acoustic data, and deploying scalable cloud and edge AI with transparent governance. By emphasizing inverter-aware analysis, drift management, and benchmark standardization, this review uniquely positions vibration-based predictive maintenance as a foundation for next-generation vehicle reliability. Full article

Reducing energy consumption in buildings presents a challenge for the construction and architectural industries. Stakeholders in the building sector require innovative products and systems to reduce energy usage effectively. Building Energy Simulation (BES) tools are essential for understanding energy-related issues during the design phase. However, the existing BES tools are often complex and costly, making them inaccessible to many architects and engineers who lack the software expertise for integrating new systems into existing Building Energy Simulation frameworks. To address this gap, the authors of this article have developed a new tool that enables early-stage evaluation of building performance. Additionally, the tool includes Water Flow Glazing (WFG) as a construction element that is part of both the facade and the building’s heating and cooling system. The authors validated the methodology by comparing the results from the new tool with those from the commercial BES tool Indoor Climate and Energy IDA-ICE 5.0 in accordance with ASHRAE standards. The same cases were tested by comparing the indoor temperature of a room with the power absorbed by the water, as measured by both tools. A WFG facade can effectively help maintain comfortable room temperatures throughout both winter and summer while producing renewable thermal energy via water heat absorption. The accuracy of this tool was validated using the normalized root mean square error between results from the new tool and those from IDA-ICE 5.0, which remained below the maximum allowable error established by ASHRAE. Validation of the tool using an experimental prototype showed that a coefficient of determination (R²) of 0.91 can be achieved through iterative refinement between the model and measured data. Full article

A thermal management system is crucial to ensure temperature uniformity in electric vehicle battery packs. Maintaining the battery system’s temperature within a safe range is critical to prolonging the service life of lithium-ion cells. This study investigates the efficiency of direct liquid immersion cooling systems for lithium-ion battery units in electric vehicles. In this work, Computational Fluid Dynamics (CFD) simulations were employed to analyze the thermal behavior of a 23-cell battery module cooled by immersion, coded by commercial software ANSYS Fluent 2025 R1. For the optimization calculations, an in -hose code was developed in in Python and implemented. The module was optimized by adjusting various design and operating parameters. Immersion cooling, achieved by submerging the battery in a cooling fluid, offers markedly higher heat transfer performance than conventional cooling techniques. The optimal temperature distribution and heat dissipation were achieved by modifying the cell length and diameter, followed by adjustments to the width, length, and height of the battery case, and finally, the coolant inlet velocity. The outcomes of this study are expected to provide valuable guidance for researchers and engineers in both academia and industry, contributing to the development of more powerful, reliable, and long-lasting electric vehicles. Full article

This study investigates an integrated solar-driven single-effect H₂O–LiBr absorption chiller powered by low-grade thermal energy. A detailed thermodynamic model, comprising a solar collector, a thermal storage tank, and an absorption cycle, was developed using the Engineering Equation Solver (EES) software V10.561. A comprehensive parametric analysis and multi-objective optimization were then conducted to enhance both the energy and exergy performance of the system. The Response Surface Methodology (RSM), based on the Box–Behnken Design, was employed to develop regression models validated through analysis of variance (ANOVA). The generator temperature (78–86 °C), evaporator temperature (2.5–6.5 °C), and absorber/condenser temperature (30–40 °C) were selected as key variables. According to the results, the single-objective analyses revealed maximum values of COP = 0.8065, cooling capacity = 20.72 kW, and exergy efficiency = 39.29%. Subsequently, the multi-objective RSM optimization produced a balanced global optimum with COP = 0.797, cooling capacity = 20.68 kW, and exergy efficiency = 36.93%, achieved under optimal operating conditions of 78 °C generator temperature, 6.5 °C evaporator temperature, and 30 °C absorber/condenser temperature. The obtained results confirm the significance of the proposed low-grade solar absorption chiller, demonstrating comparable or superior performance to recent studies (e.g., COP ≈ 0.75–0.80 and ≈35–37%). This agreement validates the RSM-based optimization approach and confirms the system’s suitability for sustainable cooling applications in low-temperature solar environments. Full article

Wide-Bandgap (WBG) semiconductors—silicon carbide (SiC) and gallium nitride (GaN)— enable high-power-density conversion, but performance is limited by where heat is generated and how it is removed. This review links device-level loss mechanisms (conduction and switching, including output-capacitance hysteresis and dynamic on-resistance) to structure-driven hot spots within the ultra-thin (tens of nanometers) two-dimensional electron gas (2DEG) channel of GaN HEMTs and to thermal boundary resistance at layer interfaces. We compare wire-bondless package concepts—double-sided cooling, embedded packaging, and interleaved planar layouts—and survey system-level cooling that shortens the conduction path and raises heat-transfer coefficients. The impact on reliability is discussed using temperature-sensitive electrical parameters (e.g., on-state VDS, threshold voltage, drain leakage, di/dt, and gate current) for real-time junction-temperature estimation and compact electro-thermal RC models for remaining-useful-life prediction. Evidence from recent literature points to interface resistance in GaN-on-SiC as a primary bottleneck, while near-junction cooling and advanced packages are effective mitigations. We argue for integrated co-design—devices, packaging, electromagnetic interference (EMI)-aware layout, and cooling—together with interface engineering and health monitoring to deliver reliable, high-density WBG systems. Full article

Air liquefaction systems are essential in cryogenic engineering and energy storage, yet their performance is often constrained by significant exergy destruction. This study develops an exergy-based assessment of the Linde–Hampson air liquefaction cycle to identify dominant sources of inefficiency and explore strategies for improvement. The analysis shows that throttling (≈41%) and compression (≈40%) represent the major contributions to exergy losses, followed by finite-temperature heat transfer (≈15%) in the recuperative heat exchanger. To mitigate these losses, fractional throttling and optimized inlet conditions are proposed, leading to reduced compressor work and improved overall efficiency. A comparative study of a two-stage throttling configuration demonstrates a decrease in throttling-related exergy destruction to approximately 30%. Reverse Pinch analysis is employed to verify the thermal coupling of hot and cold streams and to determine the minimum feasible temperature difference. The design optimization of the recuperative heat exchanger identifies an optimal velocity ratio that minimizes pressure losses and quantifies how compression pressure affects the required heat transfer surface area. The results provide a systematic framework for improving the thermodynamic performance of air liquefaction cycles, highlighting exergy analysis as a powerful tool for guiding structural modifications and functional optimization. Full article

The shift towards renewable resources has positioned agar, a natural seaweed polysaccharide, as a pivotal and sustainable material for developing next-generation energy storage technologies. This review highlights the transformative role of agar-based composites as a game-changing and eco-friendly platform for supercapacitors, batteries, and fuel cells. Moving beyond the traditional synthetic polymers, agar introduces a novel paradigm by leveraging its natural gelation, superior film-forming ability, and inherent ionic conductivity to create advanced electrolytes, binders, and matrices. The novelty of this field lies in the strategic fabrication of synergistic composites with polymers, metal oxides, and carbon materials, engineered through innovative techniques like electrospinning, solvent casting, crosslinking, 3D printing, and freeze-drying. We critically examine how these innovative composites are breaking new ground in enhancing device efficacy, flexibility, and thermal stability. Ultimately, this analysis not only consolidates the current landscape but also charts future pathways, positioning agar-based materials as a pivotal and sustainable solution for powering the future. Full article

The ocean, as one of the largest thermal energy storage bodies on earth, has great potential as a thermal-electric energy reserve. Application of the relatively fixed-temperature ocean as the heat sink, and using concentrated solar energy as the heat source, one may construct a mobile power station on the ocean’s surface. However, a traditional solar-based heat source requires a large footprint to concentrate the light beam, resulting in bulky parabolic dishes, which are impractical under ocean engineering scenarios. For buoy-sized applications, the small form factor of the energy collector can only achieve limited temperature differential, and its energy quality is deemed to be unusable by traditional spring-loaded free piston Stirling engines. Facing these challenges, a low-temperature differential free piston Stirling engine is presented. The engine features a large displacer piston (ϕ136, 5 mm thick) made of corrugated board, and an aluminum power piston (ϕ10). Permanent magnets embedded in both pistons couple them through magnetic attraction rather than a mechanical spring. This magnetic “spring” delivers an inverse-exponential force–distance relation: weak attraction at large separations minimizes damping, while strong attraction at small separations efficiently transfers kinetic energy from the displacer to the power piston. Engine dynamics are captured by a lumped-parameter model implemented in Simulink, with key magnetic parameters extracted from finite-element analysis. Initial results have shown that the laboratory prototype can operate continuously across heater-to-cooler temperature differences of 58–84 K, sustaining flywheel speeds of 258–324 RPM. Full article

Zinc oxide (ZnO) nanomaterials have emerged as promising candidates for gas sensing applications due to their high sensitivity, fast response–recovery cycles, thermal and chemical stability, and low fabrication cost. However, the performance of pristine ZnO remains limited by high operating temperatures, poor selectivity, and suboptimal detection at low gas concentrations. To address these limitations, significant research efforts have focused on dopant incorporation and polymer hybridization. This review summarizes recent advances in dopant engineering using elements such as Al, Ga, Mg, In, Sn, and transition metals (Co, Ni, Cu), which modulate ZnO’s crystal structure, defect density, carrier concentration, and surface activity—resulting in enhanced gas adsorption and electron transport. Furthermore, ZnO–polymer nanocomposites (e.g., with polyaniline, polypyrrole, PEG, and chitosan) exhibit improved flexibility, surface functionality, and room-temperature responsiveness due to the presence of active functional groups and tunable porosity. The synergistic combination of dopants and polymers facilitates enhanced charge transfer, increased surface area, and stronger gas–molecule interactions. Where applicable, sol–gel-based studies are explicitly highlighted and contrasted with non-sol–gel routes to show how synthesis controls defect chemistry, morphology, and sensing metrics. This review provides a comprehensive understanding of the structure–function relationships in doped ZnO and ZnO–polymer hybrids and offers guidelines for the rational design of next-generation, low-power, and selective gas sensors for environmental and industrial applications. Full article

Recent advances in nanotechnology, including the development of nanoparticles, thin films, and superlattices, have revitalized research in thermoelectricity by enabling independent control of thermal and electrical transport, overcoming longstanding efficiency limitations and expanding opportunities for sustainable energy generation and miniaturized device applications. Tin dioxide (SnO₂) has recently attracted increasing attention as a thermoelectric material owing to its properties, such as high-temperature chemical and structural stability, non-toxicity, and the abundance of constituent elements. Current research efforts have been directed toward enhancing its thermoelectric performance through strategies such as elemental doping, nanostructuring, strain engineering, and the development of composite systems. In this study, we investigate the effects of Mg substitutional doping on the thermoelectric characteristics of SnO₂. We synthesize undoped and Mg-doped SnO₂ nanoparticles (0.05%, 0.10%, and 0.15%) using a straightforward hydrothermal technique. The investigation of the undoped and doped materials revealed that SnO₂ possesses a tetragonal rutile-type structure, as determined through structural and morphological examination. The crystalline size of all of the samples decreases as the Mg doping concentration is increased. Hall measurement and Seebeck coefficient measurements have been employed for assessing the thermoelectric characteristics. As the Mg content increased, both the Seebeck coefficient and electrical conductivity value increased from −20 $\mathsf{\mu }$V/K to −91 $\mathsf{\mu }$V/K and 29.8 S/cm to 112.6 S/cm, confirming the presence of semiconductor behavior. The 0.15% Mg-doped sample demonstrates the highest power factor when evaluated at a temperature of 150 K, yielding a value of 9.4 $\times {10}^{-5}$ WK⁻²m⁻¹. Full article